Visual debugger for Jupyter Notebooks: Myth or Reality?

Understand how Python debuggers work and how to build Visual Debugger for Jupyter Notebooks

Elizaveta Shashkova

Debugging Jupyter Python general Tooling

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Many Python developers like Jupyter Notebooks for their flexibility: they are very useful for interactive prototyping, scientific experiments, visualizations and many other tasks. There are different development tools which make working with Jupyter Notebooks easier and smoother, but all of them lack very important feature: visual debugger. Since Jupyter Kernel is a usual Python process, it looks reasonably to use one of existing Python debuggers with it. But is it really possible?

In this talk we’ll try to understand how Python debugger should be changed to work with Jupyter cells and how these changes are already implemented in the PyCharm IDE. After that we’ll look into the whole Jupyter architecture and try to understand which bottlenecks in it prevent creation of universal Jupyter debugger at the moment.

This talk requires a basic knowledge of Jupyter Notebooks and understanding of Python functions and objects. It will be interesting for people who want to learn internals of the tools they use every day. Also it might be an inspiration for people who want to implement a visual debugger in their favourite IDE.

Type: Talk (30 mins); Python level: Intermediate; Domain level: Intermediate

Elizaveta Shashkova


Elizaveta Shashkova is a software developer of the PyCharm IDE at JetBrains. She is working on the Python debugger and Data Science tools.